void rf510_wsnamedsets()
{
   
   
 
 
   
   
 
   
   std::unique_ptr<RooDataSet> 
data{model->
generate(*
w->set(
"observables"), 1000)};
 
 
   
 
   
 
   
   w->loadSnapshot(
"reference_fit");
 
   w->loadSnapshot(
"reference_fit_bkgonly");
 
 
   
   new TCanvas(
"rf510_wsnamedsets", 
"rf503_wsnamedsets", 600, 600);
 
   gPad->SetLeftMargin(0.15);
 
 
   
 
   
}
 
{
   
   
 
   
 
   
   RooRealVar mean(
"mean", 
"mean of gaussians", 5, 0, 10);
 
 
 
   
 
   
 
   
 
   
 
   
   
 
   
   
   
   
   
   
   
   w.defineSet(
"parameters", *params);
 
   w.defineSet(
"observables", 
x);
 
 
   
   
 
   
   
   
   
   
   
   
 
   
   
 
   
   
   w.saveSnapshot(
"reference_fit", *params, 
true);
 
 
   
   
 
 
   w.saveSnapshot(
"reference_fit_bkgonly", *params, 
true);
 
}
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
 
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
 
RooFit::OwningPtr< RooArgSet > getParameters(const RooAbsData *data, bool stripDisconnected=true) const
Create a list of leaf nodes in the arg tree starting with ourself as top node that don't match any of...
 
Abstract interface for all probability density functions.
 
RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1={}, const RooCmdArg &arg2={}, const RooCmdArg &arg3={}, const RooCmdArg &arg4={}, const RooCmdArg &arg5={}, const RooCmdArg &arg6={}, const RooCmdArg &arg7={}, const RooCmdArg &arg8={}, const RooCmdArg &arg9={}, const RooCmdArg &arg10={}) const override
Helper calling plotOn(RooPlot*, RooLinkedList&) const.
 
RooFit::OwningPtr< RooFitResult > fitTo(RooAbsData &data, CmdArgs_t const &... cmdArgs)
Fit PDF to given dataset.
 
RooFit::OwningPtr< RooDataSet > generate(const RooArgSet &whatVars, Int_t nEvents, const RooCmdArg &arg1, const RooCmdArg &arg2={}, const RooCmdArg &arg3={}, const RooCmdArg &arg4={}, const RooCmdArg &arg5={})
See RooAbsPdf::generate(const RooArgSet&,const RooCmdArg&,const RooCmdArg&,const RooCmdArg&,...
 
Efficient implementation of a sum of PDFs of the form.
 
RooArgList is a container object that can hold multiple RooAbsArg objects.
 
RooArgSet is a container object that can hold multiple RooAbsArg objects.
 
Chebychev polynomial p.d.f.
 
Plot frame and a container for graphics objects within that frame.
 
void Draw(Option_t *options=nullptr) override
Draw this plot and all of the elements it contains.
 
Variable that can be changed from the outside.
 
Persistable container for RooFit projects.
 
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
 
RooCmdArg PrintLevel(Int_t code)
 
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
 
   
[#0] WARNING:InputArguments -- The parameter 'sigma1' with range [-inf, inf] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range.
[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-inf, inf] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::model
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooChebychev::bkg
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::x
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a0
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::bkgfrac
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::sig
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::mean
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sig1frac
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig2
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma2
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using generic CPU library compiled with no vectorizations
[#1] INFO:Fitting -- Creation of NLL object took 585.55 μs
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- Creation of NLL object took 182.661 μs
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#0] ERROR:Minimization -- RooMinimizer::calculateHessErrors() Error when calculating Hessian
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- Creation of NLL object took 116.52 μs
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
 
RooWorkspace(w) w contents
 
variables
---------
(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2,x)
 
p.d.f.s
-------
RooChebychev::bkg[ x=x coefList=(a0,a1) ] = 1
RooAddPdf::model[ bkgfrac * bkg + [%] * sig ] = 1/1
RooAddPdf::sig[ sig1frac * sig1 + [%] * sig2 ] = 0.999388/1
RooGaussian::sig1[ x=x mean=mean sigma=sigma1 ] = 0.999291
RooGaussian::sig2[ x=x mean=mean sigma=sigma2 ] = 0.999823
 
parameter snapshots
-------------------
reference_fit = (a0=0.500613 +/- 0.023199,a1=0.160315 +/- 0.0373121,bkgfrac=0.504699 +/- 0.0113933,mean=5.01883 +/- 0.0101222,sigma1=0.5[C],sig1frac=0.8179 +/- 0.0374037,sigma2=1[C])
reference_fit_bkgonly = (a0=0.474264 +/- 0,a1=6.8252e-12 +/- 0,bkgfrac=1[C],mean=5.01883 +/- 0,sigma1=0.5[C],sig1frac=0.8179 +/- 0,sigma2=1[C])
 
named sets
----------
observables:(x)
parameters:(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2)